Exploration of the trait analysis for trait synchrony.
Parameters: environmental correction is TRUE, correction for the region is FALSE.
Check all hypotheses between traits and environmental drivers, and among traits
| Trait_short | Driver_short | Expected | Direct/indirect | Justification | Ref | observed_corr | Fit_to_expectations |
|---|---|---|---|---|---|---|---|
| Plants | |||||||
| SLA | LUI | ++ | D | More nutrients = fast | 0.37 | ✅ | |
| LeafN | LUI | ++ | D | More nutrients = fast | 0.47 | ✅ | |
| LDMC | LUI | – | D | More nutrients = fast | -0.37 | ✅ | |
| Height | LUI | – | D | Grazing selects for short | 0.03 | Inconclusive | |
| Seed_mass | LUI | – | D | Disturbance promotes dispersal with few resources | -0.35 | ✅ | |
| Specific_root_length | LUI | ++ | D | More nutrients = fast | 0.14 | Inconclusive | |
| Fine_roots_diameter | LUI | – | D | Few nutrients = collaboration | -0.23 | ✅ | |
| Mycorrhizal_inf_int | LUI | – | D | Few nutrients = collaboration | -0.33 | ✅ | |
| Root_tissue_density | LUI | – | D | More nutrients = fast | -0.22 | ✅ | |
| Root_weight_ratio | LUI | – | D | Slow: root storage | -0.48 | ✅ | |
| Rooting_depth | LUI |
|
D | Disturbance = smaller (//height?) | 0.35 | ❌ | |
| Fine_roots_diameter | TWI | – | D | Dry = collaboration | 0.00 | Inconclusive | |
| Mycorrhizal_inf_int | TWI | – | D | Dry = collaboration | 0.00 | Inconclusive | |
| Bacteria & fungi | |||||||
| bact_motil | LUI | +/- | D | a/ disturbance promotes dispersal or b/ low nutrients mean more mouvement is needed | -0.45 | B | |
| bact_Size | Fertil. | +/- | D | a/ more nutrients makes it easier to grow or b/ slow strategy = big (copiotrophic) | -0.38 | B | |
| bact_Time | LUI | ++ | D | LUI promotes fast bacteria (but in this case overide/TWI) | 0.07 | Inconclusive | |
| bact_long | LUI | ++ | I | oligo=fast are longer | (Fierer 2007) | 0.33 | ✅ |
| bact_gensize | LUI | – | D | Slow/stress resistance = more genes | -0.25 | ✅ | |
| FB | LUI | – | D and I | Fungi slower than bacteria, linked to slow plant traits | -0.33 | ✅ | |
| CN | LUI | – | D | Less N when less nutrients available (copio have lower CN) | Fierer 2007 | -0.19 | ✅ |
| fun_spore_size | LUI | – | D | Small spores = better dispersers; Large spores have more nutrients to survive in nutrient-depleted conditions | Crandal el al. 2020, Dawson 2020; Deveautour 2020 | 0.27 | ❌ |
| AMF | LUI | ++ | D | AMF when few nutrients | -0.05 | Inconclusive | |
| AMF | TWI | – | D | AMF prefer dry | 0.00 | Inconclusive | |
| bact_anaer | TWI | ++ | D | Humidity selects anaerobic | 0.00 | Inconclusive | |
| bact_nitr | TWI | ++ | D | More nitrification in wet soils? | 0.00 | Inconclusive | |
| bact_motil | TWI | ++ | D | Easier to move if water | 0.00 | Inconclusive | |
| bact_Time | TWI | ++ | I | Anaerobics are slower | 0.00 | Inconclusive | |
| bact_spor | TWI | – | D | More reproduction through sporulation if dry | 0.00 | Inconclusive | |
| fun_spore_size | TWI | ++ | D | Thick spore walls prevent dessication | Crandal el al. 2020, Dawson 2020; Deveautour 2020 | 0.00 | Inconclusive |
| Protists (bact. + primary) | |||||||
| p1_Testate | LUI | ++ | D | Teste protects from disturbance | -0.25 | ❌ | |
| p1_Parasite | LUI | ++ | I | LUI increases plant N… | 0.47 | ✅ | |
| p1_Size | LUI | – | D | Large = slow? | -0.50 | ✅ | |
| p1_Testate | TWI | ++ | D | Teste protects from dessication | 0.00 | Inconclusive | |
| p1_Parasite | LeafN | ++ | D | and parasites enjoy | 0.48 | ✅ | |
| Protists (pred.) | |||||||
| p2_Testate | Grazing | ++ | D | Teste protects from disturbance | 0.01 | Inconclusive | |
| p2_Size | LUI | – | D | Large = slow? | -0.26 | ✅ | |
| p2_Testate | TWI | ++ | D | Teste protects from dessication | 0.00 | Inconclusive | |
| Arthropods (herbivores) | |||||||
| aH_Size | LUI | +/- | D | a/ big are also better dispersers or b/ big = slow | -0.23 | B | |
| aH_Size | Mowing | – | D | Disturbance selects for smaller | -0.20 | ✅ | |
| aH_Dispersal | LUI | ++ | D | LUI selects good dispersers | 0.25 | ✅ | |
| aH_Generalism | LUI | ++ | I | More nutrients -> generalists | 0.31 | ✅ | |
| aH_Chewers | LUI | – | I | Less nutrients = tougher plants | -0.01 | Inconclusive | |
| Arthropods (predators) | |||||||
| aH_Stratum_herb | LUI | – | D | More disturbance = less in herb | 0.31 | ❌ | |
| aC_Dispersal | LUI | ++ | D | LUI selects good dispersers | 0.37 | ✅ | |
| aC_Size | LUI | – | D | Big = slow | -0.17 | ✔ | |
| aC_Extraint | LUI | ++ | I | More resources -> parasite | -0.09 | Inconclusive | |
| aC_Stratum_herb | LUI | – | D | More disturbance = less in herb | -0.14 | Inconclusive | |
| Arthropods (details) | |||||||
| aAH_Size | LUI | +/- | D | a/ big are also better dispersers or b/ big = slow | -0.23 | B | |
| aAH_Size | Mowing | – | D | Disturbance selects for smaller | -0.20 | ✅ | |
| aAH_Dispersal | LUI | ++ | D | LUI selects good dispersers | 0.25 | ✅ | |
| aAH_Generalism | LUI | ++ | I | More nutrients -> generalists | 0.31 | ✅ | |
| aAH_Chewers | LUI | – | I | Less nutrients = tougher plants | -0.01 | Inconclusive | |
| aAC_Dispersal | LUI | ++ | D | LUI selects good dispersers | 0.32 | ✅ | |
| aAC_Size | LUI | – | D | Big = slow | -0.07 | Inconclusive | |
| aAC_Extraint | LUI | ++ | I | More resources -> parasite | -0.13 | Inconclusive | |
| aBH_Size | LUI | +/- | D | a/ big are also better dispersers or b/ big = slow | -0.33 | Inconclusive | |
| aBH_Size | Mowing | – | D | Disturbance selects for smaller | -0.26 | Inconclusive | |
| aBH_Dispersal | LUI | ++ | D | LUI selects good dispersers | 0.10 | Inconclusive | |
| aBH_Generalism | LUI | ++ | I | More nutrients -> generalists | -0.45 | ❌ | |
| aBH_Chewers | LUI | – | I | Less nutrients = tougher plants | 0.37 | X | |
| aBC_Dispersal | LUI | ++ | D | LUI selects good dispersers | 0.13 | Inconclusive | |
| aBC_Size | LUI | – | D | Big = slow | -0.09 | Inconclusive | |
| aBC_Extraint | LUI | ++ | I | More resources -> parasite | -0.03 | Inconclusive | |
| Mites (soil) | |||||||
| mitS_Sex | LUI | ++ | I | Habitat openness = sexual repro, more LUI = more growth | Salmon et al 2014 | 0.31 | ✅ |
| mitS_Mass | LUI | – | Mass = size = slow | 0.29 | ❌ | ||
| mitS_DaystoAdult | LUI | – | longer lifespan = slow | 0.17 | Inconclusive | ||
| mitS_Mass | Bulk.density | – | Smaller if pores smaller ?? | -0.01 | Inconclusive | ||
| Mites (litter+surface) | |||||||
| mitL_Sex | LUI | +/- | I | Habitat openness = sexual repro (easier to find partners). Link to other variables??? | Salmon et al 2014 | -0.22 | B |
| mitL_Mass | LUI | +/- | -0.10 | Inconclusive | |||
| mitL_Cuticule | LUI | +/- | -0.19 | b | |||
| mitL_DaystoAdult | LUI | – | longer lifespan = slow | 0.02 | Inconclusive | ||
| mitL_Size | TWI | – | D | Large = protection against dessication | 0.00 | Inconclusive | |
| mitL_Size | Temperature | – | D | Large = protection against frost | 0.00 | Inconclusive | |
| mitL_Size | Bulk.density | – | D | Smaller if pores smaller ?? | -0.17 | Inconclusive | |
| Collembola (Litter+surface) | |||||||
| colL_Size | LUI | +/- | -0.06 | Inconclusive | |||
| colL_Ocelli | LUI | +/- | 0.14 | Inconclusive | |||
| colL_Pigment | LUI | +/- | -0.02 | Inconclusive | |||
| colL_PAO | LUI | +/- | 0.01 | Inconclusive | |||
| colL_Asp | LUI | +/- | 0.06 | Inconclusive | |||
| colL_Scales | LUI | +/- | 0.03 | Inconclusive | |||
| Collembola (soil) | |||||||
| colS_Size | Bulk.density | – | D | Smaller if pores smaller | -0.16 | Inconclusive | |
| colS_PAO | LUI | +/- | 0.04 | Inconclusive | |||
| colS_PSO | LUI | +/- | -0.10 | Inconclusive | |||
| colS_Scales | LUI | +/- | 0.14 | Inconclusive | |||
| colS_Furca | Grazing | ++ | Furca = escape disturbance | 0.03 | Inconclusive | ||
## Registered S3 methods overwritten by 'car':
## method from
## influence.merMod lme4
## cooks.distance.influence.merMod lme4
## dfbeta.influence.merMod lme4
## dfbetas.influence.merMod lme4
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
### Predators
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
## lavaan 0.6-7 ended normally after 18 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 27
##
## Number of observations 150
##
## Model Test User Model:
##
## Test statistic 6.224
## Degrees of freedom 9
## P-value (Chi-square) 0.717
## lavaan 0.6-7 ended normally after 29 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 26
##
## Number of observations 150
##
## Model Test User Model:
##
## Test statistic 12.304
## Degrees of freedom 10
## P-value (Chi-square) 0.265